Grupo QuintoAndar | Senior Data Scientist

QuintoAndar; United States; Remote; USD 44,000 - 67,000; Full time

Benefits offered by this job

Remote-first model

Meal allowance

Home office allowance

Health insurance

Dental plan

Life insurance

Childcare subsidy

Wellness program

Job summary

QuintoAndar seeks a senior Data Scientist embedded in product squads to design, build, and deploy production machine learning systems powering customer-facing features such as conversational assistants, search, and recommendations. You will help shape an internal ML platform that accelerates the broader team.

The role emphasizes production deployment, experimentation, governance, and mentorship within a fast-growing startup environment.

Qualifications

• 3+ years applying data science and building ML models in production.
• Strong knowledge of regression, classification, clustering, neural nets, feature selection, cross-validation, bias-variance, and explainability.
• Experience deploying ML at scale.
• Proficiency in Python with deep learning exposure.
• Experience mentoring other data scientists and providing technical guidance.
• Excellent written and verbal English communication.

Responsibilities

• Architect, develop, and ship ML systems to production, esp. chatbots and search.
• Design experiments and translate findings into model improvements or new features.
• Analyze diverse data to refine models or create new ones.
• Prototype LL-powered apps, including prompts, guardrails, and feasibility checks.
• Mentor peers and contribute to guilds, reviews, and demos.

Skills

ML production

Python

Leadership

Experiment design

Model explainability

English communication

Education

Master's degree in ML/DS

Tools

LoRA

QLoRA

PEFT

Job description

Role overview

Join a senior Data Science role embedded directly within product squads for a large Latin American real estate technology platform. The position centers on designing, building, and deploying production machine learning systems that power customer-facing features such as conversational assistants, search, and recommendations, while helping shape an internal ML platform that accelerates the broader team.

Responsibilities

• Architect, develop, and ship machine learning systems to production, with primary use cases in chatbots and search.
• Design and execute experiments, then translate findings into model improvements or entirely new product features.
• Analyze diverse datasets—both structured and unstructured, observational and experimental—to refine existing models or create new ones.
• Apply the scientific method to prototype LLM-powered applications, including prompt experimentation, evaluating agent behavior, assessing guardrails, and validating generative AI feasibility for product use.
• Contribute actively to chapter-wide activities such as guilds, design reviews, and demos, including mentoring peers and offering technical guidance across the team.

Requirements

• A minimum of three years applying data science and building machine learning models in production.
• Strong command of core ML concepts such as regression, classification, clustering, neural networks, feature selection, cross-validation, the curse of dimensionality, bias-variance tradeoffs, and model explainability.
• Working knowledge of the engineering challenges involved in deploying and operating ML systems at scale.
• Proficiency in Python and practical exposure to deep learning techniques.
• Experience providing technical advice and leadership to other data scientists.
• Excellent written and verbal technical communication in English, paired with a willingness to share knowledge across the chapter.

Nice to have

• A master's degree (or an undergraduate degree paired with substantial industry experience) in machine learning, data science, information retrieval, ranking, recommender systems, natural language processing, or a closely related field.
• Applied experience with generative AI, including AI agents, prompt engineering, LLM fine-tuning methods (LoRA, QLoRA, PEFT), routing strategies, monitoring setups, and guardrails.
• Prior work inside fast-growing startup or scale-up environments.

Benefits and work setup

• Remote-first model with the option to work from São Paulo offices or partner coworking spaces up to twice per week, open to candidates living anywhere in Brazil.
• Competitive salary plus profit sharing.
• Meal allowance and a home office allowance.
• Health insurance, dental plan, and life insurance coverage.
• Childcare subsidy and additional support for atypical parenthood situations.
• Wellness platform membership and an employee assistance program covering mental health, social, legal, and financial support.
• Extended parental leave, plus scheduled days off on birthdays, Mother's Day, and Father's Day.
• A discount club for everyday services, educational institution discounts, and a children's reading kit.